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Results show that traditional OLTP systems mostly under-utilize the available micro-architectural resources. In-memory OLTP systems, on the other hand, process all the data in main-memory and, therefore, can omit the buffer pool. Furthermore, they usually adopt more lightweight concurrency control mechanisms, cache-conscious data structures, and cleaner codebases since they are usually designed from scratch. Hence, we expect significant differences in micro-architectural behavior when running OLTP on platforms optimized for in-memory processing as opposed to disk-based database systems. In particular, we expect that in-memory systems exploit micro-architectural features such as instruction and data caches significantly better than disk-based systems. This paper sheds light on the micro-architectural behavior of in-memory database systems by analyzing and contrasting it to the behavior of disk-based systems when running OLTP workloads. The results show that, despite all the design changes, in-memory OLTP exhibits very similar micro-architectural behavior to disk-based OLTP: more than half of the execution time goes to memory stalls where instruction cache misses or the long-latency data misses from the last-level cache (LLC) are the dominant factors in the overall execution time. Even though ground-up designed in-memory systems can eliminate the instruction cache misses, the reduction in instruction stalls amplifies the impact of LLC data misses. As a result, only 30% of the CPU cycles are used to retire instructions, and 70% of the CPU cycles are wasted to stalls for both traditional disk-based and new generation in-memory OLTP.\n<\/jats:p>","DOI":"10.1007\/s00778-021-00663-8","type":"journal-article","created":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T12:02:46Z","timestamp":1617192166000},"page":"641-665","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Micro-architectural analysis of in-memory OLTP: Revisited"],"prefix":"10.1007","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7386-768X","authenticated-orcid":false,"given":"Utku","family":"Sirin","sequence":"first","affiliation":[]},{"given":"P\u0131nar","family":"T\u00f6z\u00fcn","sequence":"additional","affiliation":[]},{"given":"Danica","family":"Porobic","sequence":"additional","affiliation":[]},{"given":"Ahmad","family":"Yasin","sequence":"additional","affiliation":[]},{"given":"Anastasia","family":"Ailamaki","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,3,31]]},"reference":[{"key":"663_CR1","unstructured":"TPC Transcation Processing Performance Council. http:\/\/www.tpc.org\/"},{"key":"663_CR2","unstructured":"Ailamaki, A., DeWitt, D.J., Hill, M.D., Wood, D.A.: DBMSs on a Modern Processor: Where Does Time Go? 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